Transcript of "Rel events final"

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+ + Social planning tool, with a recommendation engine to personalize the experience, providing discounts and targeted group deals as the primary revenue model Simple way to find things to do, that cuts through the clutter of existing event websites/competitors Opportunity: $800 million target market, based on a Groupon-like group-deal model for the events space

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 What we learned from end What we learned from event users: organizers:  Validated consumer value prop  Local event organizers need of initial idea w/ 24 of 25 efficient ways to raise awareness consumers interviewed saying & fill excess capacity they were interested in our  It difficult to know how much proposed offering they spend on user acquisition,  Advanced discovery of events they don’t track it well and are was the greatest pain point not willing to share  Interest was split among large  Daily group deals not ticketed events (i.e. concerts) appropriate for event market and smaller local events because of limited frequency  Users preferred to get  Group deals are geared personalized event towards customer recommendations via email (vs. acquisition for lifetime going to a website) value

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 We received 139 responses 1 What we learned: 1  Print media plays a more significant role in local event discovery (vs. large ticketed events and business events)  Greatest interest in our service was 2 around local events  Parents emerged as a potential archetype“; 69% of people who answered they’d “very likely” be interested in our service were married 2 with kids, (vs. 40% overall) We tried to use Facebook ads and a $25 gift card to generate more responses  While we received 20K impressions this translated into only 6 clicks and ZERO completed surveys (over 1 week)

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 What we learned from some of them:  Sonic Living  Referral revenues from concert ticket sales do not provide sufficient revenue to be a scalable startup even at scale  Lucky Cal  Similar to sonic living focused on larger ticketed events (i.e. concerts) and concluded there is not sufficient revenues from an affiliate model  Triporati  Importance of defining an event taxonomy for use in the personalized recommendations.

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 We started working with the various potential Revenue Models  Targeted and General Advertising  Excess capacity fulfillment  Lead Generation  Selling demographic data Tried to connect with business users who could help validate the millions they were going to pay us But….

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 Tough to connect with & extract info from these event organizers/business users So – it was time to seek help from our mentors and the teaching team

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 The mentors/ teaching team’s advice was to focus on users  Could we get them?  Will they interact regularly?  Will they share with friends?  Will they attend events we suggest? Validating this meant going full force on building out our user- focused Minimum Viable Product

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We started too broad  We started with all types of events – and then decided to focus on Fairs and Festivals for San FranciscoParents are not our target customer  The users who signed up through our Ad-Words campaign tended to be interested in more of the singles and couples eventsAcquiring users solely through advertising is expensive!!! ($10/user acquisition cost)  Viral user acquisition is keyUser Engagement of 60% might actually be too good to be true  Developer might have been testing Facebook share functionalitySolid technical talent that can conceptualize the business goals & communicate well is CRITICAL! (Who would have thought?)Without a Data Strategy, we are dead in the water  Scraping data at scale difficult due to data inconsistencies  Challenges in locating data sources to expand geographically

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We have customers ~40 customers in our small selected market & limited set of events We have a (feature reduced) product We provided our scrappy, hacked together, product - surprised that we were serving customersVirality is our next major hurdle and biggestconcern:•Reduction of Customer Acquisition CostsViral customer acquisition absolutely crucial to themodel, and we were unable to prove or disprove ourmechanism – will shortly•Brings scale appropriate for the revenue models

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We have to do what, …It was a lot of getting Looking back -(this is Steve? out of the building supposed to be happy)Feedback Local vs. International Talent Team Dynamics• Unexpectedly easy to obtain: • Our technical skill set was • Difficult to organize teamInterviews, surveys, lacking – turned to outsourcing quickly and effectivelycompetitors, partners, advisors to India • Class (group) vs. Real• We had trouble deciding • Cheap but more management Startup (leader driven)when to listen and when to than expected, especially with the • Our team wasignore what we were time differences dysfunctional – operationalseeing/hearing • Inability to experiment rapidly and time constrains•Real validation & tracking • Would have been worth the compounded issuesmore useful and we learned to upfront investment finding •Alignment of goals onbuild it into the product quality talent team

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User Acquisition Multi-Sided Network• Paying for traffic is easy, but not sustainable • More difficult to validate, craft a viableat $5 to $10 per user business model, and decide where to• Adwords/Facebook– only good for kicking focus firstthings off and testing hypotheses • We spent a lot of time figuring out• Need a proven mechanism for adoption where to focus next… Thank you advisors• Crafty but time consuming ways of drivingtraffic – craigslist spam, Twitter, Facebookgroups Validate then Pivot or Move Forward? • We struggled when and why a pivot might be warranted • Setting targets up front saved us time and pain, but we got smarter -eventually

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Social Planning Tool + Recommendation Engine + Discounts and Targeted Group DealsThe replacement for the community newspaper event guide –a personalized, simple way to find local events… Reduction of Risk With Next Steps Viral & Social Crowdsourced Data Revenue Model Sharing Acquisition Validation Even though our execution fell behind… we are testing the viral component next week – since it is a vital component to our model, if we don’t get 10% of users sharing recommended events with friends (or if we have unexpected results with user engagement), we pivot / quit

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Beta / Kickoff Final Model Various Sources of Incentives• Technically Local Datachallenginggiven local Crowdsourced Event • Still an We Borrowed Withoutsource Asking Data unknowndifferences given our Company or selected• More work Crowdsourced Quality feature setthan Control was to testexpected in our userdriving valuequality and Web & E-mail Event Information propositionrelevance •0from thedata • Product algorithm and event taxonomy needs refinement • Served our needs in the initial stages but likely will not scale to a broader set of events